The microRNA expression signature on modified titanium implant surfaces influences genetic mechanisms leading to osteogenic differentiation

Topographically and chemically modified titanium implants are recognized to have improved osteogenic properties; however, the molecular regulation of this process remains unknown. This study aimed to determine the microRNA profile and the potential regulation of osteogenic differentiation following early exposure of osteoprogenitor cells to sand-blasted, large-grit acid-etched (SLA) and hydrophilic SLA (modSLA) surfaces. Firstly, the osteogenic characteristics of the primary osteoprogenitor cells were confirmed using ALP activity and Alizarin Red S staining. The effect of smooth (SMO), SLA and modSLA surfaces on the TGF-β/BMP (BMP2, BMP6, ACVR1) and non-canonical WNT/Ca2+ (WNT5A, FZD6) pathways, as well as the integrins ITGB1 and ITGA2, was determined. It was revealed that the modified titanium surfaces could induce the activation of TGF-β/BMP and non-canonical WNT/Ca2+ signaling genes. The expression pattern of microRNAs (miRNAs) related to cell differentiation was evaluated. Statistical analysis of the differentially regulated miRNAs indicated that 35 and 32 miRNAs were down-regulated on the modSLA and SLA surfaces respectively, when compared with the smooth surface (SMO). Thirty-one miRNAs that were down-regulated were common to both modSLA and SLA. There were 10 miRNAs up-regulated on modSLA and nine on SLA surfaces, amongst which eight were the same as observed on modSLA. TargetScan predictions for the down-regulated miRNAs revealed genes of the TGF-β/BMP and non-canonical Ca2+ pathways as targets. This study demonstrated that modified titanium implant surfaces induce differential regulation of miRNAs, which potentially regulate the TGF-β/BMP and WNT/Ca2+ pathways during osteogenic differentiation on modified titanium implant surfaces.

miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data

miRDeep and its varieties are widely used to quantify known and novel micro RNA (miRNA) from small RNA sequencing (RNAseq). This article describes miRDeep*, our integrated miRNA identification tool, which is modeled off miRDeep, but the precision of detecting novel miRNAs is improved by introducing new strategies to identify precursor miRNAs. miRDeep* has a user-friendly graphic interface and accepts raw data in FastQ and Sequence Alignment Map (SAM) or the binary equivalent (BAM) format. Known and novel miRNA expression levels, as measured by the number of reads, are displayed in an interface, which shows each RNAseq read relative to the pre-miRNA hairpin. The secondary pre-miRNA structure and read locations for each predicted miRNA are shown and kept in a separate figure file. Moreover, the target genes of known and novel miRNAs are predicted using the TargetScan algorithm, and the targets are ranked according to the confidence score. miRDeep* is an integrated standalone application where sequence alignment, pre-miRNA secondary structure calculation and graphical display are purely Java coded. This application tool can be executed using a normal personal computer with 1.5 GB of memory. Further, we show that miRDeep* outperformed existing miRNA prediction tools using our LNCaP and other small RNAseq datasets. miRDeep* is freely available online at http://www.australianprostatecentre.org/research/software/mirdeep-star

Prediction and Verification of miRNA Expression in Human and Rat Retinas.

PURPOSE: MicroRNAs (miRNAs) play a global role in regulating gene expression and have important tissue-specific functions. Little is known about their role in the retina. The purpose of this study was to establish the retinal expression of those miRNAs predicted to target genes involved in vision. METHODS: miRNAs potentially targeting important "retinal" genes, as defined by expression pattern and implication in disease, were predicted using a published algorithm (TargetScan; Envisioneering Medical Technologies, St. Louis, MO). The presence of candidate miRNAs in human and rat retinal RNA was assessed by RT-PCR. cDNA levels for each miRNA were determined by quantitative PCR. The ability to discriminate between miRNAs varying by a single nucleotide was assessed. The activity of miR-124 and miR-29 against predicted target sites in Rdh10 and Impdh1 was tested by cotransfection of miRNA mimics and luciferase reporter plasmids. RESULTS: Sixty-seven miRNAs were predicted to target one or more of the 320 retinal genes listed herein. All 11 candidate miRNAs tested were expressed in the retina, including miR-7, miR-124, miR135a, and miR135b. Relative levels of individual miRNAs were similar between rats and humans. The Rdh10 3'UTR, which contains a predicted miR-124 target site, mediated the inhibition of luciferase activity by miR-124 mimics in cell culture. CONCLUSIONS: Many miRNAs likely to regulate genes important for retinal function are present in the retina. Conservation of miRNA retinal expression patterns from rats to humans supports evidence from other tissues that disruption of miRNAs is a likely cause of a range of visual abnormalities.

Individual mRNA expression profiles reveal the effects of specific microRNAs

BACKGROUND: MicroRNAs (miRNAs) are oligoribonucleotides with an important role in regulation of gene expression at the level of translation. Despite imperfect target complementarity, they can also significantly reduce mRNA levels. The validity of miRNA target gene predictions is difficult to assess at the protein level. We sought, therefore, to determine whether a general lowering of predicted target gene mRNA expression by endogenous miRNAs was detectable within microarray gene expression profiles. RESULTS: The target gene sets predicted for each miRNA were mapped onto known gene expression data from a range of tissues. Whether considering mean absolute target gene expression, rank sum tests or 'ranked ratios', many miRNAs with significantly reduced target gene expression corresponded to those known to be expressed in the cognate tissue. Expression levels of miRNAs with reduced target mRNA levels were higher than those of miRNAs with no detectable effect on mRNA expression. Analysis of microarray data gathered after artificial perturbation of expression of a specific miRNA confirmed the predicted increase or decrease in influence of the altered miRNA upon mRNA levels. Strongest associations were observed with targets predicted by TargetScan. CONCLUSION: We have demonstrated that the effect of a miRNA on its target mRNAs' levels can be measured within a single gene expression profile. This emphasizes the extent of this mode of regulation in vivo and confirms that many of the predicted miRNA-mRNA interactions are correct. The success of this approach has revealed the vast potential for extracting information about miRNA function from gene expression profiles.

Ranking of microRNA target prediction scores by Pareto front analysis

Over the past ten years, a variety of microRNA target prediction methods has been developed, and many of the methods are constantly improved and adapted to recent insights into miRNA-mRNA interactions. In a typical scenario, different methods return different rankings of putative targets, even if the ranking is reduced to selected mRNAs that are related to a specific disease or cell type. For the experimental validation it is then difficult to decide in which order to process the predicted miRNA-mRNA bindings, since each validation is a laborious task and therefore only a limited number of mRNAs can be analysed. We propose a new ranking scheme that combines ranked predictions from several methods and - unlike standard thresholding methods - utilises the concept of Pareto fronts as defined in multi-objective optimisation. In the present study, we attempt a proof of concept by applying the new ranking scheme to hsa-miR-21, hsa-miR-125b, and hsa-miR-373 and prediction scores supplied by PITA and RNAhybrid. The scores are interpreted as a two-objective optimisation problem, and the elements of the Pareto front are ranked by the STarMir score with a subsequent re-calculation of the Pareto front after removal of the top-ranked mRNA from the basic set of prediction scores. The method is evaluated on validated targets of the three miRNA, and the ranking is compared to scores from DIANA-microT and TargetScan. We observed that the new ranking method performs well and consistent, and the first validated targets are elements of Pareto fronts at a relatively early stage of the recurrent procedure. which encourages further research towards a higher-dimensional analysis of Pareto fronts. (C) 2010 Elsevier Ltd. All rights reserved.

Analisi di espressione di microRNA in Tumore a Cellule Giganti: identificazione dei target con ruolo di potenziali biomarcatori

Il Tumore a Cellule Giganti dell’osso (TCG) è una rara neoplasia che rappresenta il 5% dei tumori di natura ossea; sebbene venga considerato un tumore a decorso benigno può manifestare caratteri di aggressività locale dando origine a recidive locali nel 10-25% dei casi, e nel 2-4% dei casi metastatizza a livello polmonare. In questo studio è stata valutata l’espressione dei miRNA mediante miRNA microarray in 10 pazienti affetti da TCG, 5 con metastasi e 5 liberi da malattia; sono stati riscontrati miRNA differenzialmente espressi tra i 2 gruppi di pazienti e la successiva validazione mediante Real Time PCR ha confermato una differenza significativa per il miR-136 (p=0.04). Mediante analisi bioinformatica con il software TargetScan abbiamo identificato RANK e NF1B come target del miR-136 e ne abbiamo studiato l’espressione mediante Real Time PCR su una più ampia casistica di pazienti affetti da TCG, metastatico e non, evidenziando una maggior espressione di NF1B nel gruppo di pazienti metastatici, mentre RANK non ha dimostrato una differenza significativa. L’analisi di Western Blot ha rilevato una maggiore espressione di entrambe le proteine nei pazienti metastatici rispetto ai non metastatici. Successivamente è stato condotto uno studio di immunoistochimica su TMA di 163 campioni di pazienti affetti da TCG a diverso decorso clinico che ha dimostrato una maggiore e significativa espressione di entrambe i target nei pazienti con metastasi rispetto ai non metastatici; le analisi di popolazione mediante Kaplan-Meier hanno confermato la correlazione tra over-espressione di RANK, NF1B e ricaduta con metastasi (p=0.001 e p<0.0005 rispettivamente). Lo studio di immunoistochimica è stato ampliato alle proteine maggiormente coinvolte nell’osteolisi che risultano avere un significato prognostico; tuttavia mediante analisi di ROC, la co-over-espressione di RANK, RANKL e NF1B rappresenta il migliore modello per predire la comparsa di metastasi (AUC=0.782, p<0.0005).

Changes in miRNA Expression in a Model of Microcephaly

miRNAs function to regulate gene expression through post-transcriptional mechanisms to potentially regulate multiple aspects of physiology and development. Whole transcriptome analysis has been conducted on the citron kinase mutant rat, a mutant that shows decreases in brain growth and development. The resulting differences in RNA between mutant and wild-type controls can be used to identify genetic pathways that may be regulated differentially in normal compared to abnormal neurogenesis. The goal of this thesis was to verify, with quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), changes in miRNA expression in Cit-k mutants and wild types. In addition to confirming miRNA expression changes, bio-informatics software TargetScan 5.1 was used to identify potential mRNA targets of the differentially expressed miRNAs. The miRNAs that were confirmed to change include: rno-miR-466c, mmu-miR-493, mmu-miR-297a, hsa-miR-765, and hsa-miR-1270. The TargetScan analysis revealed 347 potential targets which have known roles in development. A subset of these potential targets include genes involved in the Wnt signaling pathway which is known to be an important regulator of stem cell development.